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- W2169483743 abstract "In this paper, we propose a support driven reweighted ℓ <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>1</inf> minimization algorithm (SDRL1) that solves a sequence of weighted ℓ <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>1</inf> problems and relies on the support estimate accuracy. Our SDRL1 algorithm is related to the IRL1 algorithm proposed by Candès, Wakin, and Boyd. We demonstrate that it is sufficient to find support estimates with good accuracy and apply constant weights instead of using the inverse coefficient magnitudes to achieve gains similar to those of IRL1. We then prove that given a support estimate with sufficient accuracy, if the signal decays according to a specific rate, the solution to the weighted ℓ <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>1</inf> minimization problem results in a support estimate with higher accuracy than the initial estimate. We also show that under certain conditions, it is possible to achieve higher estimate accuracy when the intersection of support estimates is considered. We demonstrate the performance of SDRL1 through numerical simulations and compare it with that of IRL1 and standard ℓ <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>1</inf> minimization." @default.
- W2169483743 created "2016-06-24" @default.
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- W2169483743 date "2012-03-01" @default.
- W2169483743 modified "2023-09-26" @default.
- W2169483743 title "Support driven reweighted ℓ<inf>1</inf> minimization" @default.
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- W2169483743 doi "https://doi.org/10.1109/icassp.2012.6288623" @default.
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